DIY Financial Advisor
by Wesley Gray, Jack Vogel and David Foulke
Wes Gray is one of my favorite financial writers. His book, Quantitative Value (written with Andrew Tobias) changed my thinking on stock market investing. I consumed it like a murder mystery, willing myself to wait to see “whodunit” while blazing through the chapters. Quantitative Momentum was excellent as well, and contributed to me changing my mind on Momentum Investing. Even so, it was with some degree of resistance that I read “DIY Financial Advisor.” As a professional financial advisor, I willingly admit that for some people the DIY option is best, but I believe the number of people who fall into that category is smaller than that of those who believe they do. Finally, I pulled the book off my shelf and devoured it on a recent reading day.
The first part of the book explores how experts can be beat. It is full of stories, studies and statistics of experts in various fields underperforming simple models. “The academic evidence is unequivocal: systematic decision making, which depends on models, outperforms discretionary decision making, or experts.” DIY does not argue that experts are worthless. Rather, it breaks the decision-making process down to three steps: 1) Research and development, 2) Systematic implementation, 3) Evidence-based assessment. Experts are useful for the first and last steps – building the system and assessing its continued effectiveness. Models are better for implementation because they are not subject to the myriad cognitive biases that afflict humans. For instance, because humans think in stories, we try to make sense of all the information available. If more information is given, it must be used somehow, even if it provides no extra value to what is already known. This leads to sub-optimal decisions. For this reason, a simple model outperforms people with much greater information. Intuitively, we would expect that an expert armed with a model would be better than either alone. The evidence contradicts this. While the performance of both experts and non-experts improves when they are given access to a model, it still trails blind reliance on the model itself. The book explains five dangerous cognitive biases: anchoring, framing, availability, physical state and overconfidence. Alarmingly, even people with knowledge of how these biases work cannot avoid including them in their thinking.
The book explores how intuitive ideas become myths – the data do not bear them out, and yet they persist because they make sense. Three specific myths are examined. The first myth is that the Warren Buffett approach (value + quality) beats the Ben Graham approach (value). Enhancing valuation decisions with information about quality seems like it should work, but the quality component dilutes the powerful value component, dragging down returns.  The second myth is that economic growth drives stock returns. There are too many other more important factors. A study of developed countries over 102 years showed no discernible correlation between economic growth and stock returns. The third myth is that companies with higher earnings retention rates have higher growth rates. This should be right if capital markets theory works perfectly. Companies that retain earnings should invest in value creating projects, boosting earnings. The evidence shows the opposite. The point of this chapter is that we should make decisions based on evidence, not intuition.
The second part of the book is on how to beat the experts using quantitative systems. It starts by looking at why people trust their financial advisors and then suggests that based on what we learned from section 1, we should not trust ourselves to accurately assess whether an advisor is trustworthy. DIY introduces the FACTS framework: Fees – what are the all-in fees? Access – how easy is it to get to your money if you need to? Complexity – “complexity does not equal value”. Taxes – what is the after-tax return? Search – how much cost and effort does it take to find the managers? Investors should understand what they are paying and what they are getting for their fees. Money should be accessible, or at least have a legitimate business reason for a lack of accessibility. The investment strategy should be as complex as necessary, but no more so. Funds should be invested to maximize after-tax return, not for pre-tax returns. The system should be designed to minimize headaches and maximize confidence in the search process.
The book examines various diversified asset allocation recommendations and concludes that diversification, and not one precise allocation is the important factor. It uses Meb Faber’s “Ivy 5 Portfolio”. This is an even split of domestic equity, international equity, real estate, commodities and fixed income. The second step is risk management. After exploring various techniques to improve downside risk, the book settles on an equal blend of time series momentum and moving average. It demonstrates over a 39-year study period that both systems improved downside risk across asset classes, without giving up return. The third step is security selection. DIY presents the compelling evidence for value investing. This works because growth rates are mean-reverting, but stocks are priced as if current growth (or lack thereof) will last indefinitely. The book cites a 50+ year study showing a value-weighted portfolio outperformed the S&P 500 by 4.2% per year, annualized. Next, momentum investing is explored. This is simply buying stocks that are already going up more than others. This is based on people’s initial underreaction to companies’ improvement (anchoring bias) and eventual overreaction (confirmation bias, herd effect). Over 87 years, the top momentum stocks outperformed the S&P 500 by 7% per year. Combining value and momentum would have done better than either alone (1963-2014) due to the diversification benefit. Over the test period, this outperformed the S&P 500 by 7.5% annualized, with identical worst drawdown (50.2%) and slightly higher standard deviation.
Finally, the book tests the system, using a 39 year backtest (1976-2014). This was a great time for both US large capitalization stocks and bonds, making the typical 60/40 portfolio very hard to beat over this time frame. Nevertheless, the basic Ivy 5 matched the total return and standard deviation of the 60/40. It did have much larger max drawdown. Applying the moving average risk management tool improved the downside risk to much better than 60/40. Finally, the security selection layer was added. The total results were impressive. The moderate portfolio outperformed the 60/40 by almost 3% annualized, with a comparable volatility and just over half the max drawdown (1992-2014)’  The implementation concludes with boosting the return by another 1% through using momentum to select real estate investment trusts monthly and trading commodities futures based on trend and the shape of the futures curve. These suggestions are beyond the ability or time-constraints of most individual investors, and even most financial advisors, and could be tax-inefficient.
Conclusion: DIY Financial Advisor is a great book for investors who are considering managing their own portfolio or for professional investment advisors. It presents a great system- one that is accessible to those with time and interest, but it is still somewhat technical and complex. It ignores much of the value a financial advisor provides, such as financial planning and behavioral coaching and focuses solely on investment management. Still, the book is a treasure in presenting the challenges investors face and a great system for dealing with these. Whether an individual decides to self-implement this strategy or to hire an advisor, this book arms investors with knowledge of what pitfalls to avoid and a robust, evidence-based approach to investing.
Wesley R. Gray, J. R. (2015). DIY Financial Advisor. Hoboken, New Jersey: WIley and Sons.
Disclaimer: This is intended for educational purposes only, and should not be construed as financial advice. Nothing stated herein should be relied upon to make investment decisions, and data referenced was from the book “DIY Financial Advisor.” Performance numbers were not independently verified. Past performance is no guarantee of future results. Any opinions expressed in this book review are the opinions of the author only and do not represent Rothman Investment Management. Investing is risky and individuals should do their own research and consult with their financial advisor before making investment decisions.
 (Wesley R. Gray, 2015), 9
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 (Wesley R. Gray, 2015), 33-47
 There is a way to use quality to improve a value-based model, but it is not by equally blending value and quality, which gives a portfolio of stocks that are not necessarily very good at either metric. There is some evidence for using the screens sequentially, sorting the cheapest ranked stocks on a quality filter.
 (Wesley R. Gray, 2015), 54-57
 (Wesley R. Gray, 2015), 57-58
 (Wesley R. Gray, 2015), 75-86
 This is based on The Ivy Portfolio by Meb Faber, which is a similar book and a great read.
 (Wesley R. Gray, 2015), 98-104
 The time series momentum rule holds an asset if its trailing return over a time period (DIY uses 12 months) exceeds the return of an alternative asset, such as Treasury bill, and sells or hedges if it is not. The simple moving average rule take the average price of the index over the last t periods (DIY uses 12) and holds the asset if the price is above the average and sells or hedges if it is not. These rules are applied at the asset class level.
 In US large-cap equities the total return using the risk management tools was identical to buy and hold, while each of the other four asset classes had higher returns with the risk management, while volatility for each asset class declined by 20-30%. (pp. 114, 116)
 (Wesley R. Gray, 2015), 134-140
 (Wesley R. Gray, 2015), 140-146
 This is 60% S&P 500, 40% US bonds, and is widely considered the generic portfolio.
 Ivy 5 with MA had a compounded annual growth rate (CAGR) of 10.98%, standard deviation of 7.35% and max drawdown of 12.65% compared to the 60/40: 10.91%, 10.03%, 25.29%
 The moderate risk DIY had a CAGR of 12.02%, standard deviation of 8.86% and worst drawdown of 13.81% compared to the 60/40: 9.23%, 8.47%, 25.29%.
 (Wesley R. Gray, 2015), 170